Day: July 29, 2010

Frontiers in Artificial Intelligence and Applications: Proceeding of the 2010 conference on Formal Ontology in Information Systems, Sixth International Conference (FOIS 2010)

Anusuriya Devaraju and Werner Kuhn

“We introduce a process-centric ontological approach to relate observed properties to geo-processes that influence those observations. These relations are used to handle semantic heterogeneities that impede the integration of geo-sensor data. Our approach comprises a process-centric hydrology ontology and its alignment with the DOLCE foundational ontology. We describe how DOLCE assists in classifying two hydrological processes and their participating entities. Our preliminary results indicate that the process-centric ontological approach can be used to resolve process and property naming ambiguity within a domain. We consider this as a first step toward a process-centric semantic integration of geo-sensor data.”

“Geographic information system (GIS), remote sensing (RS), gradient analysis, and landscape pattern metrics were coupled to quantitatively characterize the spatiotemporal change of land use and landscape pattern over the period 1988–2007 in a coastal gulf region, southeast China. The results obtained show an increase in cropland, buildup land, and aquiculture area and decrease in orchard, woodland, and beach area during 1988–2007. Landscape fragmented processes were strengthened and landscape pattern structure became more complicated in the last two decades in Luoyuan gulf region. The dynamics intensity of landscape pattern is stronger during 2002–2007 than that during 1988–2002. Spatial difference of urban–rural landscape pattern can be detected distinctively in two transects in terms of landscape metrics. Urbanization processes and the policy developed to transfer seawater into buildup land are two driving forces leading to the spatiotemporal change of landscape pattern in Luoyuan gulf region in the last two decades.”

“One of the goals of the CUAHSI Hydrologic Information System project (Maidment, 2009) is to create a comprehensive portrait of hydrologic observations for the U.S., integrating observational data and metadata from multiple sources, at the national, regional, and local levels. The data are made available via a uniform set of web service interfaces, called CUAHSI Water Data Services. Once a source of hydrologic observations is exposed via such set of methods, it is registered in the HIS Central registry (hiscentral.cuahsi.org) and its metadata is harvested into the central metadata catalog. The catalog currently indexes 9 million time series for 1.8 million measurement points, supporting web service access to about 4.3 billion data points. Such large catalogs and databases of observational and model-generated data are time consuming to query using common relational database tools. This paper describes a technique for rapid analysis and visualization of data summaries in large hydrologic data repositories using Online Analytical Processing (OLAP). OLAP databases, often called data cubes, are special representations that support high performance querying of large multidimensional data collections. The OLAP techniques are applied to the analysis of observation data catalogs and databases from several federal agencies, including EPA STORET, USGS NWIS, and USDA SNOTEL. We present sample OLAP analysis related to hydrologic data availability from the observations data catalogs, and geographic and temporal analysis of available data totals from the federal repositories. In addition, we demonstrate a novel web application for spatial analysis of OLAP data cubes built over observational and model-generated hydrologic datasets.”

“As our ability to measure the world around us improves, we are quickly generating massive quantities of high-dimensional, spatial-temporal data. In this paper, we concern ourselves with datasets in which the spatial characteristics are relatively static but many dimensions prevail and data is sampled over different time periods. Example applications include building energy management of HVAC unit diagnostics. We present methods employed in our Wakame visualization system to support such tasks as discovering anomalies and comparing performance across multiple time series. Novel methods include animated transitions that relate data in spatially located 3D views with conventional 2D graphs. Additionally, several components of our prototype employ analytics to guide the user to ”interesting” portions of the dataset.”

Arid Land Research and Management, Volume 24, Issue 3 July 2010, pages 253-262

Shoubo Li and Wenzhi Zhao

“Desert oasis wetlands are distributed along the Heihe River, especially in lowland oases along the middle reach of the river, in northwestern China. Landscape maps of the wetlands in 1990, 1995, 2000, and 2006 were compiled based on data collected from Landsat TM and ETM+ images using GIS and analyzed in July 2008. Various landscape indices were calculated using the landscape structure analysis software FRAGSTATS, at both class and landscape levels. The results showed that floodplain wetland is the dominant type of wetlands in the middle reach of the Heihe River, followed by non-forested peatland, then river and reservoir wetland, with the proportion of shrub-dominated wetland low. During these 16 years, the area of wetlands in our study area decreased by 38.4%, or 107.8 km2. The major type of wetland lost in the study area was non-forested peatland during the first five years, but floodplain wetland since then. The landscape pattern shows that the fragmentation level is very high, especially in the floodplain wetlands: the patch density increased by 154% during the study period. It is clear that the wetlands along the middle reach of the Heihe River have become increasingly fragmental during the past 16 years.”

“Across Europe, education, disadvantage and place are strongly linked. In areas characterised by high levels of disadvantage, where families most vulnerable to social exclusion are concentrated, children are most likely to achieve poor educational outcomes (Palmer et al 2007). Huge resources have been directed towards breaking this pattern – from strategies promoting school effectiveness and improvement, to area-based initiatives including France’s Zones d’Education Prioritaire, and England’s Education Action Zones (Bénabou et al 2005, Hatcher and Leblond 2001). Yet despite this, the link remains strongly ingrained. Policy’s relative failure in this respect suggests that it has been based on an inadequate understanding of the nature of educational inequities (Gulson 2005, Power et al 2005). Following this, this paper argues that policies need to be informed by spatial understanding of education inequities, which focuses attention on the local structures, processes and relationships which create these. It asks: “What can be learnt from a spatial analysis of educational inequities?” The paper reports empirical data from a spatial analysis of educational inequities in an urban inner-city ward in North West England. This has a number of ramifications – conceptually, and for research and policy: 1. It starts to develop a framework for the spatial analyses of educational inequities focusing on: (1) an area’s observable features (e.g. the locations of schools, demographic characteristics, housing types) (Butler and Hamnett 2007); (2) how areas are experienced and ‘lived’ (Lefbvre 1991); and (3) how these dimensions of space interact and impact on education. 2. It identifies the need for research which can: (1) explain how local dynamics shape educational outcomes; and (2) identify the key underlying factors at work, those which can be acted upon, and by whom. 3. It suggests that policymakers can respond to such analyses by creating broad national frameworks with some scope for strategic development at local level.”

“Grassland fire disasters have occurred frequently and adversely affected livestock agriculture and social-economic development greatly in the grassland regions of Jilin province, China. Moreover, both the frequency of grassland fire and loss from them are considered to be increasing with the global warming and economic development. This study presents a methodology for risk analysis and assessment of grassland fire disaster, taking western Jilin province as a case study area based on geographic information system (GIS). The composite grassland fire disaster risk index (GFDRI) combined the hazard of grassland fire, the exposure of the region, the vulnerability and emergency response and recovery capability for grassland fire disaster of the region were developed to assess and compare risk of grassland fire disaster in different counties in western Jilin province, China using the natural disaster risk index method (NDRIM), analytic hierarchy process (AHP) and weighted comprehensive method (WCM). Then, the risk degree of grassland fire disaster was assessed and regionalized in the western Jilin province, China based on GFDRI by using GIS. It is shown that the most places of western Jilin province were in mediate risk. Zhenlai, Tongyu were in heavy risk. Taobei, Ningjiang, Fuyu were in light risk. The information obtained from interviewing the district official committees in relation to result compiled was statistically evaluated. The GFDRI was developed to be an easily understandable tool that can be used to assess and compare the relative risk of grassland fire disaster in different counties in the western Jilin province, China, and to compare the different relative contributions of various factors, e.g., frequency of grassland fire and quality of emergency evacuation plan. The GFDRI is specifically intend to support local and national government agencies of grassland fire disaster management as they (1) make resource allocation decisions; (2) make high-level planning decisions; and (3) raise public awareness of grassland fire disaster risk, its causes, and ways to manage it. ”